Various wireless communication systems are known. Higher order modulation wireless signals such as those used in CDMA (Code Division Multiple Access) or OFDM (Orthogonal Frequency Division Multiplexing) based communication systems have a high Peak to Average signal power Ratio (PAR). The higher peaks require the communication system to operate a Power Amplifier (PA) used to transmit the signal at less than an optimal power level because the higher signal peaks can cause the PA to max-out or saturate. To allow the power amplifier for a communication system to be driven harder and more efficiently, the peak to average ratio of the transmitted signals should be reduced while preserving the other characteristics of the signal such as modulation accuracy and spectral mask requirements.
Digital PAR reduction techniques typically involve injecting noise into the signal to cancel out the time domain signal peaks, thereby reducing the PAR. Traditionally, finite impulse response (FIR) filters are used to spectrally shape the cancellation noise before applying the cancellation noise to the signal; one such approach to using an FIR filter to reduce PAR includes that described in U.S. patent application Ser. No. 10/643,179, filed Aug. 18, 2003, published as U.S. 2004/0052314, which is incorporated herein by reference. By so shaping the cancellation noise, spectral re-growth of the signal is prevented. For multi-carrier systems, using an FIR filter, however, causes the phase of the injected noise to be different from the phase of the signal, which introduces phase noise to the transmitted signal. The FIR filter should match the instantaneous spectrum of the composite multicarrier signal typical of transmit systems, otherwise mismatch between the time domain profiles of the signal peaks and the cancellation noise reduces the peak cancellation efficiency.
Moreover, the peak reduction algorithm typically needs to run at high sample rates because higher oversampling enables better fractional peak estimation. These processing requirements make the FIR filter an expensive solution in terms of hardware requirements. Additionally, multi-carrier communication signals requiring dynamic allocation of carrier frequencies, or dynamic scaling of carrier power, require the FIR filter coefficients to also be recomputed and updated on the fly, thereby requiring additional processing resources. In the absence of prior knowledge of the frequency hopping sequence for a communication signal, estimation of the new FIR filter coefficients to match the new carrier frequency allocations becomes a very hardware intensive problem.